Euclidean Nearest-Neighbor Distance (Aggregation metric)
Arguments
- landscape
Raster* Layer, Stack, Brick, SpatRaster (terra), stars, or a list of rasterLayers.
- directions
The number of directions in which patches should be connected: 4 (rook's case) or 8 (queen's case).
- verbose
Print warning message if not sufficient patches are present
Details
$$ENN = h_{ij}$$ where \(h_{ij}\) is the distance to the nearest neighbouring patch of the same class i in meters
ENN is an 'Aggregation metric'. The distance to the nearest neighbouring patch of the same class i. The distance is measured from edge-to-edge. The range is limited by the cell resolution on the lower limit and the landscape extent on the upper limit. The metric is a simple way to describe patch isolation.
References
McGarigal, K., SA Cushman, and E Ene. 2012. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical and Continuous Maps. Computer software program produced by the authors at the University of Massachusetts, Amherst. Available at the following web site: http://www.umass.edu/landeco/research/fragstats/fragstats.html
McGarigal, K., and McComb, W. C. (1995). Relationships between landscape structure and breeding birds in the Oregon Coast Range. Ecological monographs, 65(3), 235-260.
Examples
lsm_p_enn(landscape)
#> # A tibble: 27 × 6
#> layer level class id metric value
#> <int> <chr> <int> <int> <chr> <dbl>
#> 1 1 patch 1 1 enn 7
#> 2 1 patch 1 2 enn 4
#> 3 1 patch 1 3 enn 2.83
#> 4 1 patch 1 4 enn 2
#> 5 1 patch 1 5 enn 2
#> 6 1 patch 1 6 enn 2.83
#> 7 1 patch 1 7 enn 4.12
#> 8 1 patch 1 8 enn 4.12
#> 9 1 patch 1 9 enn 4.24
#> 10 1 patch 2 10 enn 4.47
#> # … with 17 more rows